Hepatocellular carcinoma (HCC) remains a health concern characterized by heterogeneity and high mortality. Surgical resection, radiofrequency ablation, trans-arterial chemoembolization, and liver transplantation offer potentially curative treatments for early-stage disease, but recurrence remains high. Most patients present with advanced-stage HCC, where locoregional therapies are less effective, and systemic treatments-primarily multi-kinase inhibitors and immune checkpoint inhibitors-often yield limited responses. Precision medicine aims to tailor therapy to molecular and genetic profiles, yet its adoption in HCC is hindered by inter-/intra-tumoral heterogeneity and limited biopsy availability. Advances in molecular diagnostics support reintroducing tissue sampling to better characterize genetic, epigenetic, and immunological features. Liquid biopsy offers a minimally invasive method for capturing real-time tumor evolution, overcoming spatial and temporal heterogeneity. Artificial intelligence and machine learning are revolutionizing biomarker discovery, risk stratification, and treatment planning by integrating multi-omics data. Immunological factors such as tumor-infiltrating lymphocytes, natural killer cells, macrophages, and fibroblasts have emerged as determinants of HCC progression and treatment response. Conversion therapy-combining systemic agents with locoregional treatments-has showndemonstrated promise in downstaging unresectable HCC. Ongoing efforts to refine biomarker-driven approaches and optimize multi-modality regimens underscore precision medicine's potential to improve outcomes. PubMed (January 2002-February 2025) was searched for relevant studies.

Hepatocellular carcinoma (HCC), which accounts for about 90% of all primary liver cancer cases, is the fifth most common malignancy and the second leading cause of cancer-related mortality worldwide. This study aims to analyse the differential costs of HCC-related hospital admissions compared to the general population in Spain.

A retrospective multicenter study analyzed inpatient admissions from a Spanish national discharge database, covering 90% of hospitals between 2010 and 2022. HCC-related admissions were identified using ICD-9 and ICD-10 codes, while control admissions were selected from the general population in the same database without an HCC diagnosis. The direct hospitalization cost was included, covering medical examinations, procedures, medications, surgeries, personnel and equipment. Statistical methods, including nearest-neighbor matching, propensity score matching, and a generalized linear model, were used to estimate differential costs and to ensure comparability based on age, gender, and Charlson Comorbidity Index (CCI).

A total of 199,670 HCC-related hospital admissions and 200,000 control admissions were analyzed. Most HCC-related admissions involved male patients (78%) aged 66-85 years, with an average CCI of 5.18. HCC-related admissions incurred significantly higher costs, with an estimated differential cost of €1,303.68 using GLM, €1,804.25 via propensity score matching, and €1,767.77 using nearest-neighbor matching. Total costs per HCC admission ranged between €1,000 and €31,000.

HCC-related hospital admissions impose a significantly higher economic burden due to the complexity of care. Given the high mortality and resource utilization, advancements in early detection, treatment, and cost-effective interventions are needed to improve patient outcomes and reduce healthcare costs.

The principal aim of the present study was to develop and validate a nomogram predicting overall survival (OS) in patients with α-fetoprotein (AFP)-negative hepatocellular carcinoma (AFP-NHCC) who experience dynamic changes in AFP level after hepatectomy. A cohort of 870 patients were enrolled and randomly assigned into a training cohort (n=600) and a validation cohort (n=270) at a 7:3 ratio. The key variables contributing to the nomogram were determined through random survival forest analysis and multivariate Cox regression. The discriminative ability of the nomogram was evaluated using time-dependent receiver operating characteristic curves and the area under the curves. Furthermore, the nomogram was comprehensively assessed using the concordance index (C-index), calibration curves and clinical decision curve analysis (DCA). Kaplan-Meier (KM) curves analysis was employed to discern survival rates across diverse risk strata of patients. Ultimately, the nomogram incorporated critical factors including sex, tumor size, globulin levels, gamma-glutamyl transferase and fibrinogen levels. In the training and validation cohorts, the C-indexes were 0.72 [95% confidence interval (CI): 0.685-0.755) and 0.664 (95% CI: 0.611-0.717], respectively, attesting to its predictive validity. The nomogram demonstrated excellent calibration and DCA further confirmed its clinical usefulness. Additionally, KM curve analysis unveiled statistically significant differences in OS among three distinct risk groups. In conclusion, the present study successfully formulated a nomogram predicting 3-, 5- and 8-year OS in patients with AFP-NHCC with dynamic changes in AFP level post-local resection. This model serves as a valuable tool for clinicians to promptly identify high-risk patients, thereby facilitating timely interventions and potentially enhancing patient survival outcomes.

Hepatocellular carcinoma (HCC) is a predominant malignant liver tumor that cannot be efficiently treated because of poor response, toxicity, and drug resistance. Ferroptosis is an iron-dependent way of cell death associated with abnormal intracellular lipid metabolism. Celastrol (Cel) has the ability to inhibit the progression of HCC by regulating multiple signaling pathways and induce ferroptosis. However, Cel exists the limitations of low water solubility, low oral bioavailability, and high organ toxicity. Cel was encapsulated in polyethylene glycol-based liposomes modified with L-arginine (Cel@Lip-Arg). Cel@Lip-Arg has a uniform size distribution (∼100 nm), high drug loading (80 %), and excellent ability to target liver cancer cells. In vitro experiments demonstrated that Cel@Lip-Arg considerably suppressed the activity of HuH7 (hepatoma) cells but had a negligible effect on L02 (normal) cells. Cel@Lip-Arg induced ferroptosis in hepatoma cells by promoting transferrin receptor expression, inhibiting system xc- and glutathione peroxidase 4, and favoring intracellular peroxide accumulation. In vivo experiments revealed that Cel@Lip-Arg plays a therapeutic role by inducing ferroptosis. Compared to Cel, Cel@Lip-Arg had a higher anti-hepatoma activity and effectively reduced the toxicity of Cel in mice. Cel@Lip-Arg-induced ferroptosis was concluded to be an attractive strategy for the precise treatment of HCC.

Notch signaling is a widely preserved communication pathway that supports essential cellular functions by allowing adjacent cells to interact. The Notch signaling pathway consists of Notch ligands (DSL proteins), Notch receptors, DNA-binding proteins, and downstream target genes. Hepatocellular carcinoma (HCC) represents the predominant cause of cancer-related deaths globally and poses a significant threat to human health. For highly malignant HCC, current treatment options, including chemotherapy, radiotherapy, immunotherapy, targeted therapies, and surgical procedures, often have poor prognoses. Therefore, there is a need to explore additional therapeutic strategies. Many studies have found that abnormal activation of the Notch signaling pathway contributes to tumor initiation and progression by promoting HCC proliferation, metastasis, stem cell-like properties, and drug resistance. In this research, we reveal the composition and activation mechanisms of the Notch signaling pathway, as well as the molecular mechanism underlying its aberrant activation in HCC. Furthermore, we summarize recent advances in targeting Notch signaling for the treatment of HCC. This review aims to highlight the promising potential of investigating the Notch pathway as a therapeutic target in HCC.

Gene interference therapy has made significant progress in the treatment of various diseases by targeting specific pathogenic genes and down-regulating the production of harmful proteins. This approach enables the precise modulation of gene expression, offering potential therapeutic benefits for conditions driven by genetic mutations or abnormal protein accumulation. Survivin, an apoptosis-inhibiting protein, plays a critical role in regulating tumor cell proliferation and preventing programmed cell death. Its overexpression in liver cancer cells is strongly associated with poor prognosis and accelerated tumor progression. RNA interference (RNAi) therapy can effectively suppress the expression of Survivin in liver cancer, inhibiting tumor cell proliferation and promoting apoptosis. In this study, four distinct GalNAc-conjugated glycopolymer siRNA delivery systems were developed. By leveraging the efficient liver-targeting capability of the GalNAc moiety, Survivin-siRNA was specifically delivered to liver cancer cells through either covalent coupling or electrostatic adsorption. In vitro experiments demonstrated the excellent gene silencing effect of these siRNA complexes, highlighting their potential as a promising therapeutic strategy for liver cancer.

As a common cancer, liver cancer imposes an unacceptable burden on patients, but its underlying molecular mechanisms are still not fully understood. Therefore, there is an urgent need to potential biomarkers and diagnostic models for liver cancer.

In this study, transcriptome and single-cell datasets related to liver cancer were downloaded from the UCSC Xena database and the Mendeley database, and differential analysis and weighted gene co-expression network analysis were used to find differentially expressed genes related to liver cancer. We used multiple machine algorithms to find hub genes related to liver cancer, and constructed new artificial neural network models based on their transcriptome expression patterns to assist in the diagnosis of liver cancer. Subsequently, we conducted survival analysis and immune infiltration analysis to explore the correlation between hub genes and immune cells, and used single-cell data to verify hub genes related to liver cancer.

This study identified MARCO, KCNN2, NTS, TERT and SFRP4 as central genes associated with liver cancer, and constructed a new artificial neural network model for molecular diagnosis of liver cancer. The diagnostic performance of the training cohort and the validation cohort was good, with the areas under the ROC curves of 1.000 and 0.986, respectively. Immune infiltration analysis determined that these central genes were closely associated with different types of immune cells. The results of immunohistochemistry and the results at the single cell level were consistent with those at the transcriptome level, and also showed obvious differences between different cell types in liver cancer and healthy states.

This study identified MARCO, KCNN2, NTS, TERT, and SFRP4 from multiple dimensions and highlighted their key roles in the diagnosis and treatment of liver cancer from multiple dimensions, providing promising biomarkers for the diagnosis of liver cancer.

This study explores the therapeutic potential of Ponicidin on Lenvatinib-resistant hepatocellular carcinoma (HCC), elucidates its mechanism in reversing Lenvatinib resistance, and provides experimental evidence for its clinical application in overcoming this resistance.

Huh7 and HCC-LM3 cells were used to construct Lenvatinib-resistant cell lines, Huh7-LR and HCC-LM3-LR. Changes in the ferroptosis pathway post-drug resistance were observed by measuring ferroptosis-related markers. The proliferation assay were assessed by CCK-8, while the migration and invasion were measured by scratch and Transwell invasion assays. In mechanistic study, chip analysis and immunoprecipitation with biotin-labeled Ponicidin, were conducted to explore how Ponicidin overcame drug resistance. Xenograft model in nude mice was established to examine Ponicidin's anti-HCC effects In vivo. Clinical specimens were used to assess the true status of patients in Lenvatinib-resistant HCC patients.

Our study reveals for the first time that ferroptosis inhibition drives Lenvatinib resistance in HCC and identifies Ponicidin as a novel KEAP1-targeting agent to reverse this process. In vitro, ferroptosis pathway was suppressed in Lenvatinib-resistant cells. Ponicidin suppressed proliferation, clonogenicity, migration, and invasion in these cells. The combination of Ponicidin and Lenvatinib significantly inhibited proliferation and reversed drug resistance by activating the ferroptosis pathway. Preliminary mechanistic studies showed that Ponicidin binds to KEAP1, stabilizing the KEAP1/NRF2 interaction, inhibiting the nuclear translocation and activation of NRF2, and thereby inducing ferroptosis to overcome Lenvatinib resistance. In vivo, the combination of Ponicidin and Lenvatinib exhibited a synergistic effect, significantly delaying tumor growth. Clinically, p-NRF2 and GPX4 expression was higher in the Lenvatinib-insensitive group, suggesting that the ferroptosis pathway was inhibited in these patients. Thus, this study demonstrated that Ponicidin promotes ferroptosis to enhances treatment sensitivity in Lenvatinib-resistant HCC cells through KEAP1/NRF2.

AST-lymphocyte ratio index (ALRI) has been proposed as a potentially prognostic indicator of liver cancer patients underwent transcatheter arterial chemoembolization (TACE) in studies, but the numbers were small and the results were controversial. In this study, we systematically assessed the prognostic value of ALRI in liver cancer patients treated with TACE by integrating meta-analysis with single-center clinical analysis.

We conducted a systematic literature search across multiple databases and evaluated the quality of included studies using the Newcastle-Ottawa Scale. We employed a fixed-effect model to calculate the pooled hazard ratio (HR) and 95% confidence interval (CI). Publication bias were evaluated using funnel plot, Begg's and Egger's tests. Concurrently, we integrated clinical data from 127 HCC patients treated with TACE at our center, employed X-tile software to ascertain the optimal cutoff value for ALRI, and analyzed the relationship between ALRI and clinical characteristics as well as overall survival (OS), using chi-square tests, Kaplan-Meier survival curves, and Cox proportional hazards models.

The meta-analysis included 7 studies, and the pooled hazard ratio (HR) indicated that elevated ALRI was significantly associated with poorer OS in liver cancer patients underwent TACE (HR = 1.75, 95% CI: 1.46-2.1, P<0.01), with no significant heterogeneity (P = 0.542, I2 = 0.00%). Clinical analysis of 127 patients further supported this finding, with patients in the high ALRI group showed significantly lower OS compared to those in the low ALRI group (1-year OS rate: 96.7% vs. 87.9%, 2-year OS rate: 61.5% vs. 42.7%; C2 = 28.006, P<0.01). Multivariate Cox regression analysis revealed that number of tumors, tumor size and ALRI were all independent prognostic factors for OS (ALRI HR = 6.456, 95%CI: 2.247-18.55, P < 0.01).

An increase in ALRI may serve as an independent prognostic indicator of poor outcomes in liver cancer patients undergoing TACE. While it offers benefits such as being non-invasive and cost-effective, further large-scale, multicenter, prospective studies are essential to validate the efficacy of ALRI and establish standardized cutoff values for clinical application.

Upregulation of phosphoglycerate mutase 5 (PGAM5) is correlated with reduced survival outcomes in hepatocellular carcinoma (HCC). PGAM5 knockdown or knockout attenuates HCC growth in in vitro and in vivo models. A novel small molecule inhibitor of PGAM5, LFHP-1c, has recently been characterized. The objective of this study was to determine if LFHP-1c effectively reduces HCC viability in cell models.

The hepatoma and HCC cell lines, HepG2 and HuH7, respectively, were treated with LFHP-1c. Label-free imaging was used to quantify growth. Cellular viability and reactive oxygen species (ROS) production were measured using luminescent or fluorescent assays. Expression of antioxidant and metabolic proteins was measured by immunoblot. HepG2 and HuH7 PGAM5 knockout cell lines were used as negative controls.

Treatment with LFHP-1c reduced cell growth and viability in HepG2 and HuH7 cell lines. Reactive oxygen species production was upregulated in both wild-type and PGAM5 knockout cell lines following LFHP-1c exposure. Cell viability was reduced following LFHP-1c treatment in PGAM5 knockout cell lines.

LFHP-1c reduces hepatoma and HCC viability and enhances ROS production, but these effects are independent of PGAM5.

This study was performed to identify crucial oncogenes modulated by DNA methylation in hepatocellular carcinoma (HCC) and look for new drugs for HCC treatment. The data of TCGA-LIHC cohort were obtained from UCSC database. Weighted gene co-expression network analysis and multiple machine learning algorithms were applied to screen the crucial prognosis-related genes in HCC. Then these genes were further screened by DNA methylation status. Ten-eleven translocation 1 (TET1) was overexpressed in HCC cell lines, and its biological functions and regulatory effects on the oncogenes were explored by qPCR, methylation-specific polymerase chain reaction, cell viability assay, Western blot, etc. Molecular docking was applied to evaluate the binding affinity between atractylenolide I (AT-I) and TET1, and the tumor-suppressive functions of AT-I were examined with both in vitro and in vivo models. In this work, 12 crucial genes related to HCC prognosis were obtained, among which six genes were with differential methylation status in HCC tissues, including AKR1B10, ALPK3, NQO1, NT5DC2, SFN, and SPP1. The expression levels of ALPK3 and NT5DC2 were positively regulated by TET1, the crucial mediator of demethylation. TET1 overexpression increased the viability and stemness of HCC cells. AT-I had good binding affinity with TET1, and repressed its activity. AT-I promoted the methylation of ALPK3 and NT5DC2 promoter regions, and reduced their expression, and repressed the growth of HCC cells. In summary, DNA methylation contributes to HCC progression, and AT-I represses the malignancy of HCC cells by inhibiting TET1-mediated abnormal DNA demethylation.

NCOA5 has been identified as a crucial factor in the progression of hepatocellular carcinoma (HCC). This study investigates the expression of NCOA5 in HCC, revealing its significant overexpression in tumor tissues compared to healthy liver tissues, as evidenced by analysis of the TCGA dataset and RT-qPCR in patient samples. Higher NCOA5 levels correlate with poor overall survival, highlighting its role as a prognostic indicator. Furthermore, our findings suggest that elevated NCOA5 is associated with resistance to sorafenib, a common chemotherapeutic agent for HCC, as shown through analysis of publicly available datasets and the establishment of sorafenib-resistant HCC cell lines. Mechanistically, NCOA5 appears to inhibit ferroptosis in HCC cells by modulating glutathione peroxidase 4 (GPX4) levels. Knockdown of NCOA5 sensitizes resistant cell lines to sorafenib and induces ferroptosis by decreasing GPX4 expression. Additionally, NCOA5 regulation of GPX4 is mediated through the transcription factor MYC. In vivo studies further validate that targeting NCOA5 enhances the efficacy of sorafenib in resistant HCC models by promoting ferroptosis. Collectively, these findings underscore the potential of NCOA5 as a therapeutic target to overcome drug resistance in HCC, providing insights into its role in modulating treatment responses and patient prognosis.

Hepatocellular carcinoma (HCC) is a severe disease associated with a poor prognosis. The role of aberrant lipid metabolism in the development and progression of HCC necessitates detailed characterization. Sterol regulatory element‑binding proteins (SREBPs), pivotal transcription factors governing lipogenesis, are central to this process. The present study aimed to assess the regulation of HCC by the SREBP signaling pathway, examining the expression levels of genes in this pathway, the clinical implications and its prognostic value using the Kaplan‑Meier method. Pearson's correlation coefficient was used to identify the co‑expression of SREBP pathway genes in HCC. Genomic analysis examined the frequency of TP53 mutations in groups with and without SREBP pathway alterations. In addition, small interfering RNAs targeting genes of the SREBP pathway were transfected into Huh‑7 and HCC‑LM3 cell lines. Subsequently, Cell Counting Kit‑8 and Transwell assays were carried out to evaluate the viability and invasion of these cells. Reverse transcription‑quantitative PCR and western blotting were performed to investigate the expression of TP53 in response to silencing of SREBP pathway genes. Dysregulation of SREBP pathway genes was detected in HCC tissues compared with in normal liver tissues, and predicted a poor prognosis. Silencing these genes reduced the viability and invasion of HCC cells. Furthermore, abnormal SREBP pathway gene expression was associated with poor survival rates, vascular invasion, advanced tumor stage and an increased incidence of TP53 mutations. By contrast, knockdown of SREBP pathway genes decreased mutant TP53 expression at both the mRNA and protein levels in HCC cells. The findings of the present study suggested that SREBP pathway genes could serve as promising prognostic biomarkers for HCC. The combined analysis of individual gene expression levels offers offer novel insights into the pathogenesis and progression of HCC.

B-mode ultrasound (US) presents challenges in accurately detecting and distinguishing between benign and malignant liver nodules. This study utilized quantitative US local attenuation coefficient slope (LACS) imaging to address these limitations.

This is a prospective, cross-sectional study in adult patients with definable solid liver nodules at US conducted from March 2021 to December 2023. The composite reference standard included histopathology when available or magnetic resonance imaging. LACS images were obtained using a phantom-free method. Nodule visibility was assessed by computing the contrast-to-noise ratio (CNR). Classification accuracy for differentiating benign and malignant lesions was assessed with the area under the receiver operating characteristic curve (AUC), along with sensitivity and specificity.

The study enrolled 97 patients (age: 62 y ± 13 [standard deviation]), with 57.0% malignant and 43.0% benign observations (size: 26.3 ± 18.9 mm). LACS images demonstrated higher CNR (12.3 dB) compared to B-mode (p < 0.0001). The AUC for differentiating nodules and liver parenchyma was 0.85 (95% confidence interval [CI]: 0.79-0.90), with higher values for malignant (0.93, CI: 0.88-0.97) than benign nodules (0.76, CI: 0.66-0.87). A LACS threshold of 0.94 dB/cm/MHz provided a sensitivity of 0.83 (CI: 0.74-0.89) and a specificity of 0.82 (CI: 0.73-0.88). LACS mean values were higher (p < 0.0001) in malignant (1.28 ± 0.27 dB/cm/MHz) than benign nodules (0.98 ± 0.19 dB/cm/MHz).

LACS imaging improves nodule visibility and provides better differentiation between benign and malignant liver nodules, showing promise as a diagnostic tool.

Enhanced computed tomography (CT) is the primary method for focal liver lesion diagnosis. We aimed to use automated machine learning (AutoML) algorithms to differentiate between benign and malignant focal liver lesions on the basis of radiomics from unenhanced CT images.

We enrolled 260 patients from 2 medical centers who underwent CT examinations between January 2017 and March 2023. This included 60 cases of hepatic malignancies, 93 cases of hepatic hemangiomas, 48 cases of hepatic abscesses, and 84 cases of hepatic cysts. The Pyradiomics method was used to extract radiomics features from unenhanced CT images. By using the mljar-supervised (MLJAR) AutoML framework, clinical, radiomics, and fusion models combining clinical and radiomics features were established.

In the training and validation sets, the area under the curve (AUC) values for the clinical, radiomics, and fusion models exceeded 0.900. In the external testing set, the respective AUC values for the clinical, radiomics, and fusion models were as follows: 0.88, 1.00, and 1.00 for hepatic cysts; 0.81, 0.90, and 0.97 for hepatic hemangiomas; 0.89, 0.98, and 0.92 for hepatic abscesses; and 0.23, 0.80, and 0.93 for hepatic malignancies. The diagnostic accuracy rates for hepatic cysts, hemangiomas, malignancies, and abscesses by radiologists in the external testing cohort were 0.96, 0.60, 0.79, and 0.66, respectively.

The fusion model based on noninvasive radiomics and clinical features of unenhanced CT images has high clinical value for distinguishing focal hepatic lesions.

Quercetin is a natural product with multiple activities, which possesses a promising antitumor effect on malignancies. The involvement of proline 4-hydroxylase II (P4HA2) in collagen synthesis is crucial in the growth of tumor cells. Apoptosis is a programmed cell death requisite for the stability of the intracellular environment. However, the relationship between quercetin and cell apoptosis, as well as the impact of P4HA2 in this connection, has not yet been specified in hepatocellular carcinoma(HCC).

The present study used HCC cells to investigate how quercetin regulates P4HA2 and influences cell proliferation and apoptosis.

The outcomes reveal that quercetin can impede the viability and growth of HCC cells and generate cell apoptosis in a dose-dependent manner. Additionally, quercetin prompts downregulation of P4HA2, leading to cell apoptosis in HCC cells, and knocking down P4HA2 can enhance this effect. Furthermore, we pretreated HCC cells with inhibitors (Z-VAD-FMK, LY294002) or activators (740Y-P) and found that the PI3K/Akt/mTOR pathway was occupied with quercetin-induced cell apoptosis.

This investigation reveals that quercetin compels apoptosis in HCC cells by diminishing P4HA2 and restraining the PI3K/Akt/mTOR axis.

Hepatocellular carcinoma (HCC) therapy still presents significant challenges, with a critical need for novel molecular targets and effective natural compound-based therapies. Despite its known oncogenic potential in other cancers, the role of SLC35F6 in HCC has not been previously reported, leaving a gap in our understanding of its function and therapeutic relevance. Here, we demonstrate that SLC35F6 is overexpressed in HCC and is associated with poor prognosis. Ulva lactuca polysaccharide (ULP), a natural extract with known antitumor properties, exerts its effects by upregulating miR-542-3p, which in turn inhibits SLC35F6 expression and significantly increases TP53 protein levels. Furthermore, TP53 is positively regulated by miR-542-3p, and our results indicate that SLC35F6 is a target gene of miR-542-3p. Knockdown of SLC35F6 in H22 and HepG2 cells markedly reduced cell growth while elevating TP53 expression, supporting SLC35F6 as a key regulatory factor in the miR-542-3p/TP53 axis. While this study did not confirm direct mutual regulation between SLC35F6 and TP53, our findings provide evidence that targeting SLC35F6 can suppress HCC progression. Collectively, these results identify SLC35F6 as a potential therapeutic target for HCC and provide mechanistic insights into its regulation through the miR-542-3p/SLC35F6/TP53 axis.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. The hypoxic microenvironment in HCC enhances glycolysis and co-directed lactate accumulation, which leads to increased lactylation. However, the exact biological pattern remains to be elucidated. Therefore, we sought to identify hypoxia-glycolysis-lactylation (HGL) prognosis-related signatures and validate this in vitro.

Transcriptomic data of patients with HCC were collected from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Differentially expressed HGL genes between HCC and normal tissues were obtained by DEseq2. The consensus clustering algorithm was employed to stratify patients into two distinct clusters. Subsequently, the single sample Gene Set Enrichment Analysis (ssGSEA), Tumor Immune Estimation Resource (TIMER) and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to assess immune infiltration and immune evasion. Least Absolute Shrinkage and Selection Operator (LASSO) and COX regression analysis were used to identify an HGL prognosis-related signature. Based on spatial transcriptome and histological data, we analyzed the expression of these genes in HCC and explored the function of Homer Scaffold Protein 1 (HOMER1) in HCC cells.

We identified 72 differentially expressed HGL genes and two HGL clusters. Cluster2, with better survival (p < 0.001), was significantly enriched in metabolic-related pathways. The HGL prognosis-related signature exhibited great predictive efficacy for patients in TCGA, ICGC, and GSE148355 databases (3-year area under the curve (AUC) = 0.822, 0.738, and 0.707, respectively). The elevated expression of HOMER1 in HCC was revealed by the combination of spatial transcriptome and histological data. Knocking down HOMER1 significantly inhibited the malignant progression of HCC cells.

We identified a signature with great predictive efficacy and discovered a gene, HOMER1, that influences the malignant progression of HCC with the potential to become a novel therapeutic target.

Hepatocellular carcinoma (HCC) resists immunotherapy due to its immunosuppressive microenvironment. Sarcoma homology 2 domain-containing protein tyrosine phosphatase-1 (SHP-1) inhibits T cell receptor signaling, and its pharmacological inhibition is limited by poor selectivity and membrane permeability. Here, we generated CRISPR-edited SHP-1-knockout (KO) CD8+ T cells to enhance adoptive therapy against HCC. Single-cell RNA sequencing of HCC patient T cells revealed elevated SHP-1 in exhausted subsets. SHP-1-KO T cells exhibited increased effector memory T cells (TEM) proportions and enhanced IFN-γ/Granzyme B/perforin secretion, improving cytotoxicity against HCC lines. In humanized PDX models, SHP-1-KO T cells demonstrated superior tumor-killing activity. Transcriptomics identified upregulated lipid metabolism pathways, with HMGCR as a hub gene. Combining SHP-1-KO T cells with simvastatin (HMGCR inhibitor) synergistically amplified anti-HCC efficacy. This study proposes a dual strategy combining SHP-1-targeted cell therapy and metabolic modulation to overcome immunotherapy resistance, offering a translatable approach for HCC treatment.

Hepatocellular carcinoma (HCC) is a major contributor to cancer-related deaths globally. The progression of HCC is influenced by a range of intrinsic and extrinsic factors, necessitating further research into the molecular mechanisms involved. While Regulator of G-protein Signaling 14 (RGS14) has shown emerging roles in cancer biology, its function in HCC remains poorly characterized.

RGS14 expression and clinical significance were analyzed using TCGA-LIHC, HCCDB, and GEO datasets. Immunofluorescence (IF) staining was employed to validate protein expression. Functional assays, including cell proliferation, migration, invasion, and in vivo xenograft models, were conducted to assess the oncogenic role of RGS14. Bulk-mRNA sequencing was performed using in situ tumor tissues to identify RGS14-regulated pathways.

RGS14 was significantly upregulated in HCC tissues and positively associated with poor patient outcomes. In vitro experiments demonstrated that RGS14 enhanced HCC cell proliferation, migration, and invasion, while in vivo studies confirmed its tumor-promoting effects. Mechanistically, RGS14 activated the extracellular matrix (ECM)-receptor interaction pathway to drive HCC progression.

Our findings suggest that RGS14 could serve as a novel prognostic marker and therapeutic target for HCC, contributing to improved treatment strategies.

The mitochondrial solute carrier family 25 (SLC25) is known to play a pivotal role in oncogenesis, yet its specific involvement in hepatocellular carcinoma (HCC) remains poorly elucidated.

In this study, we performed a clustering analysis of HCC patients in the Cancer Genome Atlas database based on the expression levels of SLC25 members, and conducted clinical feature analysis for each patient within the clusters. Subsequently, we developed a prognostic model using a Lasso regression approach with SLC25A19, SLC25A49, and SLC25A51 as features, and generated a risk score for each HCC patient. We then identified SLC25A19 as a potential prognostic marker for HCC through single-cell analysis, and validated this finding using in vitro and in vivo experiments.

Our results revealed significant differences in the expression of most SLC25 family members in HCC patients, enabling the stratification of patients into three clusters, with those in cluster 1 exhibiting the most favorable prognosis and showing a correlation with enhanced immune infiltration. The risk scores derived from the features SLC25A19, SLC25A49, and SLC25A51 effectively predicted the prognosis of HCC patients, with area under the curve (AUC) values exceeding 0.7 in the test group. Single-cell analysis further demonstrated h eightened expression of SLC25A19 in the immune microenvironment of HCC, and in vitro experiments indicated that SLC25A19 may regulate the proliferation, migration, invasion, cycle, and apoptosis of liver cancer cells through the Wnt pathway. In the HepG2 animal model, overexpression of SLC25A19 significantly promotes tumor growth, while knockdown inhibits tumor growth. Analysis of patient tumor tissues shows that SLC25A19 is highly expressed in liver cancer tissues and is associated with CD8+ T cell infiltration.

In conclusion, our comprehensive analysis of the role of SLC25 in HCC unveiled SLC25A19 as a potential regulatory factor in HCC.

Nanotechnology has great potential and advantages in the treatment of hepatocellular carcinoma (HCC), but the research trends and future directions are not yet clear.

Analyze the development trajectory, research hotspots, and future trends of nanotechnology and HCC research globally in the past 20 years, providing a more comprehensive and intuitive reference for researchers in this field.

Retrieve relevant literature on nanotechnology and HCC research in the Web of Science (WOS) Core Collection database, and conduct bibliometric analysis using software such as CiteSpace, VOSviewer, and SCImago Graphica.

A total of 852 English publications meeting the criteria were retrieved from the WOS database, with an overall increasing trend in the number of publications and citation frequency over the years. China leads in the number of publications and international collaborations, followed by the USA and India. The most influential research institution is the Chinese Academy of Sciences, the most influential scholar/team is the Rahman, Mahfoozur team, and the journal with the most publications is the International Journal of Nanomedicine. A comprehensive analysis reveals that the current main research directions include new types of nanoparticles, targeted drug delivery systems, photothermal/photodynamic therapy, gene delivery systems, diagnostics, and imaging. It is anticipated that further collaboration among scholars, institutions, and countries will accelerate the development of nanotechnology in the field of HCC research.

This study provides an in-depth analysis of the research status and development trends of nanotechnology in treating HCC from a bibliometric perspective, offering possible guidance for researchers to explore hot topics and frontiers, select suitable journals, and partners in this field.

Resistance to platinum-based chemotherapy agents like oxaliplatin (OXA) poses significant challenges in the treatment of cancers such as hepatocellular carcinoma (HCC). Centrin 2 (CETN2), which functions in nucleotide excision repair (NER) of DNA damage, is overexpressed in HCC. We investigated the potential role of CETN2 in modulating the sensitivity of HCC cells to OXA. CETN2 expression correlated with decreased OXA sensitivity in Huh7 and Hep3B HCC cell lines. CETN2 forms a complex with XPC, which is crucial for the initial DNA damage recognition in NER, thereby enhancing NER and reducing the efficacy of OXA. siRNA-mediated knockdown of CETN2 increased OXA-induced cytotoxicity and apoptosis, confirming its role in chemoresistance. Moreover, overexpression of CETN2 inhibited OXA-induced DNA damage, an effect partially reversed by XPC knockdown. Our findings highlight CETN2 as a potential biomarker and therapeutic target in overcoming OXA resistance in HCC and suggest the possibility for CETN2 inhibitors in enhancing chemotherapeutic efficacy in the treatment of HCC.

Liver HCC is the second leading cause of cancer-related deaths worldwide. The heterogeneity of this malignancy is driven by a wide range of genetic alterations, leading to a lack of effective therapeutic options. In this study, we conducted a systematic multi-omics characterization of HCC to uncover its metabolic reprogramming signature.

Through a comprehensive analysis incorporating transcriptomic, metabolomic, and lipidomic investigations, we identified significant changes in metabolic pathways related to glucose flux, lipid oxidation and degradation, and de novo lipogenesis in HCC. The lipidomic analysis revealed abnormal alterations in glycerol-lipids, phosphatidylcholine, and sphingolipid derivatives. Machine-learning techniques identified a panel of genes associated with lipid metabolism as common biomarkers for HCC across different etiologies. Our findings suggest that targeting phosphatidylcholine with saturated fatty acids and long-chain sphingolipid biosynthesis pathways, particularly by inhibiting lysophosphatidylcholine acyltransferase 1 ( LPCAT1 ) and ceramide synthase 5 ( CERS5 ) as potential therapeutic strategies for HCC in vivo and in vitro. Notably, our data revealed an oncogenic role of CERS5 in promoting tumor progression through lipophagy.

In conclusion, our study elucidates the metabolic reprogramming nature of lipid metabolism in HCC, identifies prognostic markers and therapeutic targets, and highlights potential metabolism-related targets for therapeutic intervention in HCC.

Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. We aimed to develop a model with multimodal features (MMF) using artificial intelligence (AI) approaches to enhance the performance of HCC detection.

A total of 1092 participants were enrolled from 16 centers. These participants were allocated into the training, internal validation, and external validation cohorts. Peripheral blood specimens were collected prospectively and subjected to mass cytometry analysis. Clinical and radiological data were obtained from electrical medical records. Various AI methods were employed to identify pertinent features and construct single-modal models with optimal performance. The XGBoost algorithm was utilized to amalgamate these models, integrating multimodal information and facilitating the development of a fusion model. Model evaluation and interpretability were demonstrated using the SHapley Additive exPlanations method.

We constructed the electronic health record, BioScore, RadiomicScore, and DLScore models based on clinical, radiological, and peripheral immunological features, respectively. Subsequently, these single-modal models were amalgamated to develop an all-in-one MMF model. The MMF model exhibited enhanced performance compared to models comprising only single-modal features in detecting HCC. This superiority in performance was confirmed through the internal and external validation cohorts, yielding area under the curve (AUC) values of 0.985 and 0.915, respectively. Additionally, the MMF model improved the detection ability in subpopulations of HCCs that were negative for alpha-fetoprotein and those with small size, with AUC values of 0.974 and 0.996, respectively.

Integrating MMF improved the performance of the model for HCC detection.

Direct-acting antivirals (DAAs) have revolutionized hepatitis C virus (HCV) treatment. The changing landscape of hepatocellular carcinoma (HCC) in liver transplant (LT) recipients lacks a thorough description of the outcomes of HCC based on etiology.

To assess the waitlist (WL) dropout and graft survival in HCC LT candidates based on the etiology of HCC in the post-DAA era.

This retrospective cohort study analyzed United Network Organ Sharing/Organ Procurement Transplant Network data from 2015 to 2022. Graft survival was analyzed using Kaplan-Meier curves, and predictors of WL dropout and graft failure were assessed using multivariate analysis.

Among LT recipients, etiologies were HCV (53.6%), alcohol-associated liver disease (ALD) (12.0%), metabolic dysfunction-associated steatotic liver disease (MASLD) (16.6%), hepatitis B virus (HBV) (5.6%), and other (12.1%). MASLD and ALD had the highest dropout rates (1-year: 20.4%, 21.7%; 3-year: 58.2%, 51.1%; P  < 0.001). Dropout was linked to diabetes, low albumin, high Model of End-Stage Liver Disease, high alpha-fetoprotein, tumor number, and size. MASLD had the worst 1-, 3-, and 5-year graft survival (89.8%, 81.8%, and 74.1%) and higher failure risk than HCV (hazard ratio: 1.143, 95% CI: 1.021-1.281). Diabetes negated MASLD's impact on graft failure but worsened survival for MASLD-HCC compared with HBV and ALD, matching HCV.

MASLD has the highest WL dropout and post-LT graft failure among HCC LT candidates, surpassing HCV in the post-DAA era. The worst graft survival in MASLD-HCC is associated with pre-LT diabetes.

Primary liver cancer is a major global health challenge, of which hepatocellular carcinoma is the most common. For patients with advanced liver cancer, Sorafenib is a first-line targeted drug that occupies a dominant position in clinical applications. Sorafenib is a multi-kinase inhibitor commonly used in clinical practice, which can effectively inhibit tumor cell proliferation, promote cell apoptosis, and inhibit angiogenesis. However, the emergence of drug resistance has hindered the development of treatment programs, which is an urgent problem to be solved. Recent studies have revealed many mechanisms and influencing factors of Sorafenib resistance (such as epigenetic regulation, programmed cell death, metabolic reprogramming, and tumor microenvironment changes). This review not only summarizes the above mechanisms, but also summarizes the combined application of Sorafenib with other drugs (such as molecular targeted drugs, other anti-angiogenesis drugs, cytotoxic drugs, immunotherapy drugs, etc .). Finally, potential strategies and research directions to overcome drug resistance (such as targeting epigenetic pathways or metabolic reprogramming) are discussed to provide suggestions for future in-depth research and clinical applications.

Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths worldwide. Aurora kinase B (AURKB), a critical regulator of mitosis, has been implicated in cancer progression, though its precise role in HCC remains unclear. In this study, AURKB expression was found to be significantly elevated in HCC tissues and cell lines compared to controls, as validated by GEPIA and ENCORI databases. Functional assays revealed that AURKB knockdown reduced cell proliferation, invasion, and migration, while increasing apoptosis. Furthermore, suppression of AURKB affected epithelial-mesenchymal transition (EMT) markers, decreasing vimentin and N-cadherin levels and increasing E-cadherin expression. In vivo, a xenograft mouse model demonstrated that tumors derived from AURKB-silenced cells exhibited reduced growth and fewer lung metastases. Histological and immunohistochemical analyses showed lower levels of Ki-67, MMP-9, and EMT markers in these tumors, alongside increased E-cadherin. These findings highlight AURKB's critical role in promoting HCC progression, metastasis, and EMT regulation. Overexpression of AURKB was associated with poor prognosis, suggesting it could serve as a potential biomarker and therapeutic target for liver cancer. Overall, targeting AURKB may provide a novel approach to inhibit HCC growth and metastasis, improving patient outcomes.

Durvalumab plus tremelimumab (Dur/Tre) is a first-line systemic treatment option for unresectable hepatocellular carcinoma (uHCC). However, the management of severe immune-mediated adverse events (imAEs) is challenging. Therefore, we investigated the relationship between severe imAEs and antitumor responses in patients with uHCC treated with Dur/Tre.

We included 157 patients with uHCC treated with Dur/Tre in this multicenter, retrospective study and analyzed the relationship between progression-free survival (PFS)/antitumor response and severe imAEs requiring high-dose corticosteroid treatment.

Thirty-two patients (20.4%) developed severe imAEs, including enterocolitis/diarrhea (n = 10), liver injury (n = 9), interstitial lung disease (n = 5), rashes (n = 4), cytokine-release syndrome/fever (n = 2), pancreatitis (n = 2), and others (n = 4) (median follow-up period, 6.8 months). Infliximab was administered in six patients with steroid-refractory enterocolitis. Although the objective response rate (ORR) and disease control rate (DCR) were significantly higher with first-line therapy than with later-line therapy (p = 0.026), the frequency of severe imAEs was not significantly different (p = 0.221). The ORR and DCR in patients with and without severe imAEs were 15.6% and 17.6% and 65.6% and 47.2%, respectively, with no significant differences. Five patients with severe imAEs, including rashes and liver injury, showed objective responses (partial response + complete response). Among patients who achieved an objective response, the PFS at 10 months was good (100% and 70.3% with and without high-dose corticosteroids, respectively).

Severe imAEs of Dur/Tre treatment requiring high-dose corticosteroid treatment did not affect antitumor efficacy, which differed depending on the type of imAEs. Therefore, appropriately managing imAEs is essential to guide sequential treatment.

Background:Alchornea laxiflora (Benth.) Pax & K. Hoffm. (A. laxiflora) is utilized as a traditional herb for treating several diseases. Objective: Our study aims to identify the active phytochemical candidates from A. laxiflora and analyses to predict their anticancer activity mechanism by employing network pharmacology, molecular docking, and molecular dynamics (MD). Methods: The phytoconstituents of A. laxiflora were retrieved from the literature, and phytoconstituent-related targets implicated in hepatocellular carcinoma (HCC) were collected from respective databases. Computational methods were employed to recognize essential compounds, hub gene targets, and signaling pathways. Results: Our study has identified 12 potentially bioactive compounds, 150 potential anti-HCC targets, and 15 hub gene targets for A. laxiflora. Molecular docking results recognized the better binding energy values of below -5.6 kcal/mol. Further, MD simulations of the three of the top-scoring protein-ligand complexes (MAPK-3-acetylursolic acid, AKT1-quercetin, and AKT1-3-acetylursolic acid) allowed us to validate the docking results, evaluate the stability of the complexes, and associated conformational changes. Conclusions: Our research claims that phytoconstituents of A. laxiflora are crucial for treating liver cancer, and the recognized protein targets can serve as biomarkers, respectively.

Negative regulator of ubiquitin-like protein 1 (NUB1), an inhibitor of neural precursor cells expressed developmentally downregulated 8 (NEDD8), is implicated in tumor growth. However, the expression of NUB1 in hepatocellular carcinoma (HCC) and its effects on HCC growth remain unclear. In this study, our findings revealed reduced NUB1 protein expression in HCC tissues and cells, leading to increased proliferating cell nuclear antigen (PCNA) protein stability through upregulating NEDD8 to promote HCC cell growth. Mechanistically, NUB1 reduction upregulated NEDD8 to promote PCNA NEDDylation at lysine 164 (Lys164), in turn, antagonized PCNA K48-linked polyubiquitination, thereby increasing the stability of PCNA in HCC cells. Finally, the results of the in vitro and in vivo experiments revealed that the NEDDylation inhibitor TAS4464 could inhibit PCNA NEDDylation to decrease PCNA protein expression, thereby suppressing HCC cell growth. Collectively, our results identified NUB1 as a negative regulator of HCC proliferation and confirmed that PCNA NEDDylation promotes PCNA protein stability by antagonizing PCNA polyubiquitination. This study provides a new perspective on the specific mechanism of HCC growth. It expands our understanding of the role of NEDDylation in the regulation of substrate proteins and their functions.

The unfolded protein response (UPR) is an adaptive and cytoprotective sensing-signaling network. Numerous studies have indicated the crucial role of UPR in the anti-tumor drug resistance and the modification of tumor microenvironment (TME). The aim of this study is to analyze the alterations of microenvironment and key regulatory genes in hepatocellular carcinoma (HCC) with high UPR activity.

We profiled differentially expressed genes (DEGs) by UPR activity, and the biological functions of DEGs and the alterations of signaling pathways were explored. The Immune/Stromal scores and relative abundance of infiltrating cells of HCC tissues with RNA sequencing data downloaded from The Cancer Genome Atlas (TCGA) were calculated by the xCell and ESTIMATE algorithm. The correlations between the prognostic UPR-related genes with the microenvironment scores and infiltrating cells were analyzed using R package "corrplot".

Our results demonstrated that UPR-related genes mainly involved in immune-related signaling pathways. Microenvironment analysis revealed that HCC tissues with higher UPR activity had lower Stromal scores and the relative abundance of various infiltrating cells including hematopoietic stem cells (HSC), lymphatic endothelial cells (LECs), microvascular endothelial cells, endothelial cells (ECs) and adipocytes decreased most significantly. Kaplan-Meier survival analysis indicated that the decline of Stromal scores and corresponding infiltrating stromal cells would result in worse prognosis. The expression levels of CLEC3B, RAMP3, GPR182 and DNASE1L3 were significantly positively correlated with Stromal scores and various infiltrating stromal cells, and down-regulation of these genes were also associated with worse prognosis of HCC.

HCC with high UPR activity had lower Stromal scores and worse prognosis. Down-regulated genes CLEC3B, RAMP3, GPR182 and DNASE1L3 may play an important regulatory role in the modification of microenvironment of HCC with high UPR activity.

Immune cells within the tumor microenvironment impact cancer progression, resistance, response to treatments. Despite remarkable outcomes for some cancer patients, immunotherapies remain unsatisfactory for others. Here, we designed an experimental setting using the Alb-R26 Met "inside-out" mouse model, faithfully recapitulating molecular features of liver cancer patients, to explore the effects of distinct anticancer targeted therapies on the tumor immune landscape. Using two treatments in clinical trials for different cancer types, Decitabine and MEK+BCL-XL blockage, we show their capability to trigger tumor regression in Alb-R26 Met mice and to superimpose distinct profiles of immune cell types and immune-checkpoints, impacting immunotherapy response. A machine learning approach processing tumor imaging and immune profile data identified a putative signature predicting tumor treatment response in mice and patients. Outcomes exemplify how the tumor immune microenvironment is differentially reshaped by distinct anticancer agents and highlight the importance of measuring its modulation during treatment to optimize oncotherapy and immunotherapy combinations.

CD161, encoded by the killer cell lectin-like receptor B1 (KLRB1) gene, exhibits varied roles among different tumors. This study aimed to explore both the potential value of CD161 as a prognostic biomarker for hepatocellular carcinoma (HCC) and its association with immune cell infiltration.

A total of 109 HCC patients who underwent surgery were retrospectively analyzed. Immunohistochemistry, bioinformatic analyses, and statistical measurements were used to investigate the associations between CD161 expression, immune cell infiltration, and clinical outcomes in both public databases and in-house cohorts.

CD161 was highly expressed at both protein and mRNA levels in adjacent normal tissues compared to tumor tissues of HCC patients. Meanwhile, CD161 was enriched in HCC cases characterized by smaller tumor sizes (≤5 cm) and the absence of portal vein tumor thrombus. Individuals with high CD161 expression showed extended overall survival (OS) and relapse free survival (RFS) compared to those with lower CD161 levels. CD161 was identified as an independent prognostic indicator for both OS and RFS. In addition, the enrichment analysis indicated a close correlation between CD161 and immune response, as well as between CD161 and the signaling pathways of cytokines and chemokines, implying its role in immune regulation during cancer development. Specifically, CD161 expression was positively associated with immunomodulators and tumor-infiltrating immune cells, especially CD8+T cells, CD4+T cells, and dendritic cells. Multiple public databases showed that patients with high CD161 expression were more likely to derive benefits from immunotherapy.

CD161 was identified as a promising prognostic biomarker for HCC, as its expression indicates a favorable prognosis. Additionally, CD161 is closely linked to high infiltration of immune cells, participates in the regulation of the tumor immune microenvironment, and holds promise as a potential biomarker for predicting the efficacy of immunotherapy.